SOTAVerified

Graph Generation

Graph Generation is an important research area with significant applications in drug and material designs.

Source: Graph Deconvolutional Generation

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 481–490 of 712 papers

TitleStatusHype
Graph-wise Common Latent Factor Extraction for Unsupervised Graph Representation LearningCode0
Neural Belief Propagation for Scene Graph Generation—0
Reinforcement Learning Enhanced Explainer for Graph Neural Networks—0
Joint Modeling of Visual Objects and Relations for Scene Graph Generation—0
Not All Relations are Equal: Mining Informative Labels for Scene Graph Generation—0
Scene Graph Generation with Geometric Context—0
Network Generation with Differential Privacy—0
Extend, don’t rebuild: Phrasing conditional graph modification as autoregressive sequence labellingCode0
Improving Query Graph Generation for Complex Question Answering over Knowledge Base—0
Outlining and Filling: Hierarchical Query Graph Generation for Answering Complex Questions over Knowledge GraphsCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1RNNStreetMover0.03—Unverified
2GraphRNNStreetMover0.02—Unverified
3GGT without CAStreetMover0.02—Unverified
4GGTStreetMover0.02—Unverified